A robust MPPT approach based on first-order sliding mode for triple-junction photovoltaic power system supplying electric vehicle

Hamed, Salah Beni; Abid, A.; Hamed, Mouna Ben; Sbita, Lassaâd; Bajaj, Mohit; Ghoneim, Sherif S. M.; Zawbaa, Hossam M.; Kamel, Salah

doi:10.1016/j.egyr.2023.02.086

Cited by 37 publications

(15 citation statements)

References 25 publications

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“…Expanding on the findings of reference 50 , the study emphasizes the existing lack of WBG devices and highlights the urgent requirement for their incorporation into EV fast-charging applications. In order to strengthen the theoretical basis of the suggested model, a comprehensive small-signal model for the converter is explained 66 . This model is crucial in developing a control approach that aims to achieve both the intended power-sharing dynamics and the overall stability and dependability of the charging system 67 .…”

Section: Related Workmentioning

confidence: 99%

Hybrid multimodule DC–DC converters accelerated by wide bandgap devices for electric vehicle systems

Waheed,

Rehman,

Alsaif

et al. 2024

Sci Rep

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In response to the growing demand for fast-charging electric vehicles (EVs), this study presents a novel hybrid multimodule DC–DC converter based on the dual-active bridge (DAB) topology. The converter comprises eight modules divided into two groups: four Insulated-Gate Bipolar Transistor (IGBT) modules and four Metal–Semiconductor Field-Effect Transistor (MESFET) modules. The former handles high power with a low switching frequency, while the latter caters to lower power with a high switching frequency. This configuration leverages the strengths of both types of semiconductors, enhancing the converter’s power efficiency and density. To investigate the converter’s performance, a small-signal model is developed, alongside a control strategy to ensure uniform power sharing among the modules. The model is evaluated through simulation using MATLAB, which confirms the uniformity of the charging current provided to EV batteries. The results show an impressive power efficiency of 99.25% and a power density of 10.99 kW/L, achieved through the utilization of fast-switching MESFETs and the DAB topology. This research suggests that the hybrid multimodule DC–DC converter is a promising solution for fast-charging EVs, providing high efficiency, power density, and switching speed. Future studies could explore the incorporation of advanced wide bandgap devices to handle even larger power fractions.

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Section: Related Workmentioning

confidence: 99%

Hybrid multimodule DC–DC converters accelerated by wide bandgap devices for electric vehicle systems

Waheed,

Rehman,

Alsaif

et al. 2024

Sci Rep

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“…GA is an algorithm that is based on the population genetics concept. Each solution represents a chromosome, while each parameter corresponds to a gene 79,82,83 . GA employs an objective (fitness) function to assess the fitness of every single population member.…”

Section: Genetic Algorithm (Ga)mentioning

confidence: 99%

A new intelligently optimized model reference adaptive controller using GA and WOA-based MPPT techniques for photovoltaic systems

Deghfel,

Badoud,

Merahi

et al. 2024

Sci Rep

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Recently, the integration of renewable energy sources, specifically photovoltaic (PV) systems, into power networks has grown in significance for sustainable energy generation. Researchers have investigated different control algorithms for maximum power point tracking (MPPT) to enhance the efficiency of PV systems. This article presents an innovative method to address the problem of maximum power point tracking in photovoltaic systems amidst swiftly changing weather conditions. MPPT techniques supply maximum power to the load during irradiance fluctuations and ambient temperatures. A novel optimal model reference adaptive controller is developed and designed based on the MIT rule to seek global maximum power without ripples rapidly. The suggested controller is also optimized through two popular meta-heuristic algorithms: The genetic algorithm (GA) and the whale optimization algorithm (WOA). These meta-heuristic approaches have been exploited to overcome the difficulty of selecting the adaptation gain of the MRAC controller. The reference voltage for MPPT is generated in the study through an adaptive neuro-fuzzy inference system. The suggested controller’s performance is tested via MATLAB/Simulink software under varying temperature and radiation circumstances. Simulation is carried out using a Soltech 1sth-215-p module coupled to a boost converter, which powers a resistive load. Furthermore, to emphasize the recommended algorithm’s performance, a comparative study was done between the optimal MRAC using GA and WOA and the conventional incremental conductance (INC) method.

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“…When grids are attached to EVs, the local distribution network faces disturbances from charging devices like power quality (PQ) factors in voltage fluctuations, voltage imbalances, and harmonics (Jargstorf and Wickert, 2013). The integration of EVs with the grid introduces challenges to power quality parameters, such as voltage imbalances, fluctuations, and harmonics, impacting the local distribution network (Liu et al, 2013b;Sun et al, 2019;Hamed et al, 2023). Numerous studies have been dedicated to addressing and mitigating the adverse effects of EV chargers on power quality (Jian et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Unified power quality conditioner-based solar EV charging station using the GBDT–JS technique

Prasada Rao,

Pandian,

Reddy

et al. 2024

Front. Energy Res.

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This manuscript proposes a novel hybrid artificial intelligence (AI) approach for a unified power quality conditioner (UPQC) designed specifically for electric vehicle charging stations (EVCSs). The aim is to integrate multiple vehicle-to-grid (V2G) functionalities, thereby mitigating the challenges associated with electric vehicle (EV) grid integration and the incorporation of distributed energy resources (DERs). The hybrid technique presented in this manuscript combines the gradient boosting decision tree (GBDT) algorithm and the jellyfish search (JS) algorithm, referred to as the GBDT–JS technique. This innovative approach involves utilizing the charging station to offer EV charging services and facilitating the discharge of EVs to the power grid. Integration of the UPQC with DERs, such as photovoltaic (PV), is implemented to decrease the power rating of converters and fulfill power demand requirements. The initial converter within the UPQC is employed to manage the direct current (DC) voltage, while the second converter oversees the power charging or discharging processes of EVs. Additionally, it mitigates the impact of battery voltage fluctuations. The UPQC with vehicle-to-grid functionality minimizes the load pressure on the grid, preventing over-current issues. The presented approach regulates the UPQC converters to mitigate power quality issues such as harmonic currents and voltage sags. Subsequently, the effectiveness of this technique is demonstrated using the MATLAB/Simulink operating platform. The evaluation of GBDT–JS performance involves a comparative analysis with existing techniques. This assessment reveals that the proposed method effectively alleviates power quality issues, specifically reducing total harmonic distortion (THD), and delivers optimal outcomes.

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A robust MPPT approach based on first-order sliding mode for triple-junction photovoltaic power system supplying electric vehicle

Cited by 37 publications

References 25 publications

Hybrid multimodule DC–DC converters accelerated by wide bandgap devices for electric vehicle systems

Hybrid multimodule DC–DC converters accelerated by wide bandgap devices for electric vehicle systems

A new intelligently optimized model reference adaptive controller using GA and WOA-based MPPT techniques for photovoltaic systems

Unified power quality conditioner-based solar EV charging station using the GBDT–JS technique

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